Mobile Edge Caching (MEC) [1]}, [2]} is an emerging technology in the Beyond Fifth Generation (5G) communication networks (also referred to as 6G) developed to meet the phenomenal growth of the global mobile data traffic. Enabling caching at the edge of the network provides the opportunity to store popular content at the storage of the heterogeneous next generation Node B (hgNB) during the off-peak intervals [3]}, [4]}. After requesting a content by an edge (e.g., Internet of Thing (IoT)) device, this request is directly served by the neighboring hgNBs, having the requested content. In such scenarios, the cache-hit occurs; otherwise, it is known as a cache-miss and the requested content is sent from the content server to the hgNB to serve the request [5]}, [6]}. Integrating Unmanned Aerial Vehicles (UAVs) as the flying hgNBs into the terrestrial MEC networks [7]} extends the service coverage and improves the Quality of Service (QoS) of User Equipment (UE) in the Beyond 5G networks. Due to the limited local storage capacity of cache-enabled hgNBs, it is of significant importance to identify/store the most popular content to enhance the cache efficiency of the network. In the MEC networks, there are two types of caching strategies, i.e., Reactive caching and proactive caching. Conventional reactive caching schemes [8]}, such as First-In-First-Out (FIFO), Least Recently Used (LRU), and Least Frequently Used (LFU) frameworks, identify the most popular content based on the underlying pattern of observed users' requests. A critical drawback of reactive caching is that popular content can only be identified after being requested. As a consequence, they are not robust to the dynamically changing behavior of the content popularity. Therefore, the main focus of recent researches has been shifted to use proactive caching, e.g., using Deep Neural Networks (DNN) models to predict the Content Popularity (CP) from the request patterns. In this context, popular content can be dynamically allocated in the storage of hgNBs before being requested. The paper aims to further advance this emerging field.
